Add Go1 evaluation and keyboard control

robogauge/tasks/robots/__init__.py

@@ -5,3 +5,4 @@ from .go2.go2_lab_config import Go2LabConfig, Go2LabTerrainConfig
 from .go2.go2 import Go2
 from .go2.go2_moe_config import Go2MoEConfig, Go2MoETerrainConfig
 from .go2.go2_moe import Go2MoE
+from .go1 import Go1Config, Go1TerrainConfig, Go1, Go1MoEConfig, Go1MoETerrainConfig, Go1MoE

robogauge/tasks/robots/go1/__init__.py

@@ -0,0 +1,4 @@
+from .go1_config import Go1Config, Go1TerrainConfig
+from .go1 import Go1
+from .go1_moe_config import Go1MoEConfig, Go1MoETerrainConfig
+from .go1_moe import Go1MoE

robogauge/tasks/robots/go1/go1.py

@@ -0,0 +1,13 @@
+# -*- coding: utf-8 -*-
+"""Go1 policy adapter.
+
+The trained policy and the Go1 MuJoCo asset both use FR, FL, RR, RL joint
+groups. Isaac Gym exposed the training asset as FL, FR, RL, RR, but Go1Robot
+permuted its observations and actions during training.
+"""
+
+from robogauge.tasks.robots.go2.go2 import Go2
+
+
+class Go1(Go2):
+    pass

robogauge/tasks/robots/go1/go1_config.py

@@ -0,0 +1,38 @@
+# -*- coding: utf-8 -*-
+"""Go1 configuration for the RoboGauge MuJoCo evaluator."""
+
+from robogauge.tasks.robots.go2.go2_config import Go2Config
+
+
+class Go1Config(Go2Config):
+    robot_name = 'go1'
+    robot_class = 'Go1'
+
+    class assets(Go2Config.assets):
+        robot_xml = "{ROBOGAUGE_ROOT_DIR}/resources/robots/go1/go1.xml"
+        foot_geom_names = ['FR', 'FL', 'RR', 'RL']
+
+    class control(Go2Config.control):
+        model_path = "{ROBOGAUGE_ROOT_DIR}/resources/models/go1/policy.pt"
+        control_dt = 0.02
+        p_gains = [28.0] * 12
+        d_gains = [0.7] * 12
+
+        # Both this MuJoCo model and the trained policy use FR, FL, RR, RL.
+        # Go1Robot permuted Isaac Gym's FL, FR, RL, RR asset state into this
+        # order during training, so applying that permutation again here
+        # would swap every left/right leg pair.
+        default_dof_pos = [
+            -0.1, 0.8, -1.5,
+             0.1, 0.8, -1.5,
+            -0.1, 1.0, -1.5,
+             0.1, 1.0, -1.5,
+        ]
+        mj2model_dof_indices = list(range(12))
+
+
+class Go1TerrainConfig(Go1Config):
+    class commands(Go1Config.commands):
+        lin_vel_x = [-1.0, 1.0]
+        lin_vel_y = [-1.0, 1.0]
+        ang_vel_yaw = [-1.5, 1.5]

robogauge/tasks/robots/go1/go1_moe.py

@@ -0,0 +1,8 @@
+# -*- coding: utf-8 -*-
+"""MoE Go1 policy adapter."""
+
+from robogauge.tasks.robots.go2.go2_moe import Go2MoE
+
+
+class Go1MoE(Go2MoE):
+    pass

robogauge/tasks/robots/go1/go1_moe_config.py

@@ -0,0 +1,12 @@
+# -*- coding: utf-8 -*-
+"""MoE policy configuration for the trained Go1 checkpoint."""
+
+from robogauge.tasks.robots.go1.go1_config import Go1Config, Go1TerrainConfig
+
+
+class Go1MoEConfig(Go1Config):
+    robot_class = 'Go1MoE'
+
+
+class Go1MoETerrainConfig(Go1TerrainConfig, Go1MoEConfig):
+    robot_class = 'Go1MoE'